Chuan-Wang Chang

Physiological emotion analysis using support vector regression

Physical and mental diseases were deeply affected by stress and negative emotions. In general, emotions can be roughly recognized by facial expressions. Since facial expressions may be controlled and expressed differently by different people subjectively, inaccurate are very likely to happen. It is hard to control physiological responses and the corresponding signals while emotions are excited. Hence, an emotion recognition method that considers physiological signals is proposed in this paper. We designed a specific emotion induction experiment to collect five physiological signals of subjects including electrocardiogram, galvanic skin responses (GSR), blood volume pulse, and pulse. We use support vector regression (SVR) to train the trend curves of three emotions (sadness, fear, and pleasure). Experimental results show that the proposed method achieves high recognition rate up to 89.2%.

Extracting significant repeating figures in music by using quantized melody contour

To extract music features from the raw data of music object and organize them as the music indices is important for music retrieval. A repeating pattern is a series of notes which appear more than once. Most of the repeating patterns are themes or tones for people to remember easily. A figure is defined as a melody contour of a musical segment. A sequence pattern is a melody segment that has the same figure with other melody segments. In this paper, we use the idea of interval between two adjacent notes to form quantized melody contour for representing music objects. This representation differs from existing methods that use notes to form a melody string. We also propose a method to find significant repeating figures. These figures could cover most of the repeating patterns that are in a noted melody string. In addition, the number of repeating figures found in samples of music is less than that of repeating patterns. As a result, the total execution time and memory space can be dramatically decreased.

An efficient authentication protocol for virtual subnets on mobile ad hoc networks

Mobile Ad hoc networks are composed of self-organizing, multi-relaying nodes connected by wireless links that the virtual subnet technology provides support to reduce redundant transmission for efficient communication is necessary. In order to satisfy security requirements, a node of virtual subnet need to identify the other member nodes, hence the certificate and authentication of virtual subnets must be established to distinguish the member nodes and the unallied nodes. In this paper, an efficient authentication protocol for virtual subnets on mobile ad hoc networks is proposed to aim for the efficiency of certificate and authentication. For the purpose, nodes of a virtual subnet have their private key respectively and they share a public key to reduce the authentication overhead and improve the efficiency. According to protocol analysis, the proposed protocol will show that it is robust with respect to certificate and authentication and very suitable for virtual subnet communication on wireless ad hoc networks.

An improved music representation method by using harmonic-based chord decision algorithm

We develop an algorithm for chord decision for monophonic music, and it can be applied to music indexing and automatic composition systems. The basic ideas of the proposed algorithm can be divided into two phases: the local recognition phase and the global decision phase. The algorithm analyzes the music and assigns a set of chord candidates in the local recognition phase, while deciding the best appropriate chord according to the chord progression rules in the global decision phase. In order to improve the perceptual accuracy, we consider the beat of corresponding notes in a measure and eliminate the effect of the passing notes and ornaments

A harmonic-based algorithm for monophonic music chord decision

With the development of multimedia technology, digital music is now in widespread use. In this paper, we develop an algorithm for chord decision for tonal music, and it can be applied to music indexing and automatic compositional system. The basic ideas of the proposed algorithm can be divided into two phases: the local recognition phase and the global decision phase. The algorithm analyzes the music and assigns a set of chord candidates in the local recognition phase, while deciding the best appropriate chord according to the chord progression rules in the global decision phase. In order to improve the perceptual accuracy, we consider that the beat of corresponding notes in a measure and eliminate the effect of the passing notes and ornaments.

An improved path sensitization method in test pattern generation for combinational circuits

We present a fast sensitized path decision method for test pattern generation of combinational circuits. This method accelerates any path sensitization test pattern generation (ATPG) algorithm, such as D-algorithm, PODEM, FAN, or SOCRATES. The essential idea of our method is to propagate the fault on a stem (fanout node) to all its fanout-branches and to desensitize one or more input lines of a reconvergent gate when the fault effect can not propagate through the gate. In this way, the time for selecting paths to be sensitized can be reduced.

PROSTATE DISEASES DIAGNOSIS IN POWER DOPPLER SONOGRAPHY

In order to detect early prostate cancer, physicians usually apply the ultrasound imaging to visualize prostate for diagnosis. However, the traditional gray-scale ultrasound images that obtained from transrectal ultrasound of the prostate are often limited in diagnosing prostate cancer because of cancer heterogeneity, which makes direct diagnosing on the image difficult. Power Doppler ultrasound images improve the diagnosis by providing extra information of blood flow. Previous study has shown that increased blood inflow exists in prostate cancer. It is not difficult to differentiate the malignancy from benign prostate diseases by inspecting Doppler spectrum at bilateral neurovascular bundle sites and using resistive index. Although it is effective; however, it is hand-held, time-consuming, and only limited in a small and static region, which might not represent the real status of the whole prostate. Therefore, this study proposed an integrated dynamic approach to estimate the resistive index of blood flow in regions of interest within or all over the whole prostate. Merits of the proposed approach include the follows: resistive index can be calculated in serial prostate frames; the calculation can be performed on integral prostate region; and the proposed approach shortened the time needed to complete the calculation on whole prostate. Experimental results show that dynamic resistive index is better than conventional resistive index, and comparable with Prostate specific antigen (PSA) test in diagnosing prostate cancer, indicating high performance of the proposed approach, which also reveals feasibility and effectively of it.

Using Incremental Addition to Evaluate the Grouping Quality of Document Classification

Most previous research on document classification assigned only one or two category tags to each document. Furthermore, the tagged items are rarely incorporated into their topic groups in subsequent classification work though it would conceivably enhance classification efficiency. with the modularity method, this research incrementally adds the classified documents to their topic groups after the recognition process to examine the changes in grouping quality. the result shows that social network analysis demonstrates great potential for automatic document classification, especially in identifying citation networks embedded in research papers and reference lists. a modified TF-IDF technique calculates the weight of each keyword in the topic groups. All the papers under study are collected from three journals in IEEE Computer Society collection published from 1979 to 2011.

A Heuristic Approach for Music Segmentation

Music segmentation is an important and essential step for successful development of music information retrieval system, particularly for polyphonic music database. In the past, most researchers assume music is monophonic. If the music is polyphonic, there is not satisfyingly solved by existing known algorithms. In this paper, we base on the LBDM and propose a heuristic method to extract the representative fragments of melody from different tracks. The extracted represented fragments are sentence-like phrases that can server as indexes of music. Experiments show the satisfying results in the proposed method.

An Efficient Numeric Indexing Technique for Music Retrieval System

Space requirement for storing indexes and performance for query processing are two critical issues in music information retrieval (MIR) system. To overcome difficulties in variable length of queries and enhance efficiency of music retrieval, we propose an effective and efficient numeric indexing structure. It differs greatly from preexisting researches in textual indexing techniques. We show how the development of this framework has been motivated and demonstrate how the technique may be naturally applied to solve this two fundamental MIR issues. Experiments are performed to compare our method with previous solutions. The results show that our method is more scalable and economical than previous methods. The method we proposed can achieve dramatically and significantly improvement in saving time and storing space for retrieving and indexing